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Title: Clustering in attributed weighted nodes network using a stochastic block model with application to EEG data Authors:  Yousri Slaoui - University of Poitiers (France) [presenting]
Abir El Haj - L@bISEN, Vision-AD, ISEN Yncrea Ouest, Caen (France)
Pierre-Yves Louis - AgroSup Dijon University of Bourgogne Franche-Comte (France)
Cyril Perret - University of Poitiers (France)
Abstract: The aim is to cluster networks with attributed weighted nodes. This question is motivated by the need to specify different electrophysiology stable periods performed by the brain during a psycho-linguistic experience, preparation of handwriting from the electrical activity produced by neurons in the brain and recorded by the electroencephalogram. The aim is to explore the evolution of the average intensity of the obtained clusters over time by classifying the 128 electrodes obtained by the electroencephalographic (EEG) recordings. We develop a stochastic block model (SBM) with several attributes to estimate the parameters of the model and to classify the nodes. Finally, we perform a numerical application using the electroencephalographic data to validate the proposed approach.